Somewhat Resilient

Last Update: 8/30/2026

AI Resilience Score for Helpers--Roofers:

44.7%

Median Score

Meaningful human contribution

High

Long-term employer demand

Low

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient roofing helper work is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For roofing helpers, five of eight sources had data. The AI exposure sources mostly agreed: AI Resilience Model and Microsoft both rated human contribution as High, with Will Robots Take My Job slightly lower at Medium, so confidence lands at Medium. Strong hands-on resilience helps, but low demand and pay signals weigh the score down, leaving this work "Somewhat Resilient."

AI Resilience Report forHelpers--Roofers

$44,160 median salary600 annual openingsSOC Code: 47-3016.00

Helpers--Roofers are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.

Helpers on roofing crews earn the "Somewhat Resilient" label because the physical, hands-on nature of the work (hauling materials, clearing debris, and working on unpredictable outdoor job sites) is genuinely hard for today's AI and robots to handle, keeping human helpers in high demand. At the same time, real changes are coming: drones and AI tools are already handling inspections and measurements, and robots like Rufus can now install shingles faster than a human, so some tasks helpers once did by hand are shifting.

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This role is somewhat resilient

Helpers on roofing crews earn the "Somewhat Resilient" label because the physical, hands-on nature of the work (hauling materials, clearing debris, and working on unpredictable outdoor job sites) is genuinely hard for today's AI and robots to handle, keeping human helpers in high demand. At the same time, real changes are coming: drones and AI tools are already handling inspections and measurements, and robots like Rufus can now install shingles faster than a human, so some tasks helpers once did by hand are shifting.

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Analysis of Current AI Resilience

Helpers--Roofers

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Helpers--Roofers jobs?

If you're worried that a robot is about to take over the helper's job on a roofing crew, take a breath — the evidence says that day is still a long way off. A large Microsoft study covered by industry trade press [1] ranked "helpers–roofing" as #25 on the list of the 40 occupations least exposed to AI, with the researchers noting that the least-impacted occupations include ones that require physically working with people, operating or monitoring machinery, and other manual labor. Most of the tasks helpers do — hauling shingles up a ladder, sweeping debris, clearing gutters, heating tar — are physical, outdoors, and constantly changing, which is exactly where today's AI struggles.

That doesn't mean nothing is changing. AI is already being used for quicker and more accurate inspections, measurements and estimates, so helpers may spend less time locating worn areas by hand and more time following a drone's map. On the robotics side, Renovate Robotics' "Rufus" [2] uses a cable-and-computer-vision system to install shingles alongside crews rather than replace them, and since its debut in 2023, Rufus has improved dramatically, with performance nearly quadrupling and the robot now 50% faster than human installers, while Renovate Robotics plans to double that speed again by the end of the year.

Trade associations are also leaning in — the National Roofing Contractors Association launched "NRCA AI" [3] in May 2026 to help members quickly search technical roofing guidance. So far, this looks much more like augmentation — tools that help the crew — than automation replacing the helper.

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AI Adoption

How fast is AI adoption growing for Helpers--Roofers?

Adoption in the office is moving fast, but adoption on the roof is moving slowly, and both trends are good news for helpers. A ServiceTitan industry report [1] covered by Roofing Contractor found that adoption of AI among commercial contractors surged from 17% to 38% in a single year, with AI being applied to core functions such as cost estimation and budgeting (24%) and bid management (22%). Those are back-office tasks — not the physical helper work.

The main drivers pushing contractors toward any automation are cost and worker scarcity. Rising labor and overhead costs, material price increases and ongoing workforce shortages continue to challenge margins, with 71% of contractors reporting rising wages [1], up from 55% the previous year, and industry commentators point out that finding and retaining skilled roofers remains one of the toughest obstacles [4] for contractors, with many crews stretched thin and younger workers hesitant to take on such a demanding, dangerous trade. That means helpers are needed, not surplus.

What's slowing physical automation down? Roofs are messy, sloped, weather-beaten worksites where every job is a little different, and robots like Rufus are expensive to buy, transport, and maintain compared with hiring a helper who earns a 2025 median wage of $46,680 per year, or $22.44 per hour [5]. There are also safety, insurance, and OSHA rules that must catch up before a robot can work unsupervised.

Meanwhile, the U.S. Bureau of Labor Statistics projects that overall employment of construction laborers and helpers is projected to grow 6 percent from 2025 to 2035 [5], faster than the average for all occupations, and industry workforce reports note that labor consistently ranks first among contractor concerns [6], with warnings that failure to attract needed workers will accelerate industrywide labor cost escalation. Translation: crews want more helpers, not fewer. Learning to work with drones, apps, and eventually robots like Rufus [7] is a smart way to stay valuable — but the human hands, judgment, and safety awareness a helper brings to a roof aren't going anywhere soon.

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Will AI replace Helpers--Roofers?

Will AI replace Helpers--Roofers?

Not entirely. We think AI will take over some tasks, but not the whole job.

Our 44.7% AI Resilience Score reflects that reality. The physical work at the core of this role, hauling shingles, clearing debris, heating tar on a sloped and weather-beaten roof, is exactly where today's AI and robotics struggle most. A large Microsoft study ranked helpers-roofers among the 40 occupations least exposed to AI, specifically calling out manual labor and physically working with people as hard for AI to touch [1].

That said, the job is changing. Drones and AI tools are already handling inspections and measurements, and robots like Rufus can now install shingles alongside crews [2]. Helpers who learn to work with these tools will be more valuable, not less. AI adoption among contractors is also rising fast in back-office areas like estimating and bid management [1], but that is office work, not roof work.

The bigger concern is the economic picture. Wages and career flexibility for this role score lower than average, and the long-term job market outlook is uncertain despite real demand today. Labor shortages keep crews stretched thin [4], so helpers are needed now. The honest advice: build physical skills, get comfortable with new tools, and keep an eye on where the trade is heading.

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Latest AI news for Helpers--Roofers

These articles highlight the resilience of roofing careers, including helpers, in the face of AI advancements. For instance, the Microsoft study shows that roofing jobs are among the least vulnerable to automation, suggesting a stable future for workers. Additionally, AI-powered tools, like smart glasses, enhance safety and efficiency on the job, allowing roofers to perform inspections and communicate better. As contractors increasingly adopt AI, helpers can benefit from improved workflows and opportunities to upskill, ensuring they remain valuable in the evolving industry.

More Career Info

Career: Helpers--Roofers

They assist roofers by carrying materials, removing old roofing, and cleaning up to ensure roofs are built or repaired efficiently and safely.

Employment & Wage Data

Median Wage

$44,160

Jobs (2025)

6,100

Growth (2025-35)

-0.1%

Annual Openings

600

Education

No formal educational credential

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

95% ResilienceCore Task

Place tiles, nail them to roof boards, and cover nailheads with roofing cement.

2

95% ResilienceCore Task

Provide assistance to skilled roofers installing and repairing roofs, flashings, and surfaces.

3

94% ResilienceCore Task

Cover roofs with layers of roofing felt or asphalt strips before installing tile, slate, or composition materials.

4

94% ResilienceCore Task

Attach roofing paper and composition shingles, using nails.

5

94% ResilienceCore Task

Attach sheets of metal to roof boards or building frameworks when installing metal roofs.

6

94% ResilienceCore Task

Apply shingles, gravel, or asphalt over the top layer of tar to protect the roofing material.

7

93% ResilienceCore Task

Remove old roofing materials.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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